In this paper I will provide an overview of some of the challenges faced
by the UK Data Archive in accessioning and processing mixed methods
collections, i.e., those comprising quantitative and qualitative data. I
will discuss issues pertaining to: data preparation including issues of
case-linkage and anonymity; descriptive/cataloguing requirements;
documentation or user guide preparation; and staff skill and training
requirements. Two case studies will be used to illuminate the problems
and solutions.

Practical Viability of Multiple Imputation as a Tool for Disclosure Protection for Large Scale Recurring Surveys

Pat Doyle (U.S. Census Bureau)

[abstract]

The literature often cites potential threats to the continued viability
of microdata products arising from the increased availability of
administrative data in the public domain and the decreased barriers to
access by individuals not skilled in data processing. Yet demand for
such products continues to rise as research and public policy demands on
data become more sophisticated and require more in-depth analysis of
the complexities of modern society. If the threat becomes real and the
demand for microdata continues, the social science community will need
an alternative to the traditional microdata products.

Current research toward replacements for public use microdata files
includes, among other options, proposals to disseminate analytically
valid synthetic microdata. To date the research has focused on the
methodology and on experiments designed to determine validity of the
approach. There is another area of research needed to determine whether
such methods can gain acceptance as a production tool by the data
producers and the data users in the statistical community. In
particular, producers need to understand what they can do to ensure
users will have faith in the quality of the estimates derived from
synthetic data.

This presentation solicits feedback on the concept of disseminating
synthetic data generated from a multiple imputation synthesizing
methodology currently under development.

Peter Burnhill (EDINA National Data Centre and University Data Library)

Robin Rice (EDINA National Data Centre and University Data Library)

[abstract]

The Digital Curation Centre (DCC; www.dcc.ac.uk)
has been established and funded by the UK government to provide
leadership to the academic community on the related problems of
scientific data curation and the long-term digital preservation of
scholarly output. The funders awarded the bid to a consortium of four UK
institutions, led by the University of Edinburgh, to provide a range of
services for the initial three years of the centre's funding. The other
partners are the University of Glasgow's Humanities Advanced Technology
and Information Institute, the Council for the Central Laboratory of
the Research Councils at Rutherford and Daresbury Appleton Laboratories,
and the UK Office for Library and Information Networking at Bath. Each
site will contribute a different expertise to the Centre, which is
currently in the set-up phase of its operation.

This paper will describe how a widely distributed partnership is being managed to achieve several 'proper tensions:'

between the needs of the hard sciences, which represent
one end of the continuum, and the needs of the soft disciplines of the
social sciences and humanities along the other end;

between the need for cutting edge research which will
improve the state of knowledge about preservation and database curation,
and the need for quick development of tools tuned to the immediate
needs of the users; and

among a vast array of international standards efforts and
preservation tools developed under hugely disparate circumstances, all
of which will be in competition for certification or publicity by the
Centre, to be rubber-stamped (or not) as deserving adoption by
communities of practice.

Peter Burnhill, Director (Phase One) of the DCC
during the set-up phase, will outline some of the drivers behind the
decision to set-up the Centre, the strategy being adopted to engage such
a diverse range of communities, and the approach being taken to make an
organisation from four partner institutions, drawing upon experience
gained in setting up the EDINA National Data Centre nine years ago.

Robin Rice, Phase One Project Coordinator, will describe what
the social sciences have both to offer and to learn from the other
disciplines in the emerging fields of data curation and digital
preservation, with a focus on the current state of the art and the
challenges ahead.

Historical research increasingly uses and produces data, and archiving
of these data is relevant for the same reasons that archiving of social
science data is relevant. Actually, archiving of historical research
data also raises some issues that are not that pressing when dealing
with social science data.

Discussions between the institutions that archive historical data were
quite vivid 10 to 15 years ago but until recently there has been a
period of silence. Some of the archives involved are trying to remedy
that, because cooperation is as relevant when archiving historical data
as when archiving social science data. Actually, there is a broad area
of common problems between Social Science Data Archives and History Data
Archives and many of the Social Science Data Archives are to greater or
lesser extent custodians of historical research data.

Over the past several years, developments in technology and
research have changed the ways in which libraries and their users interact
with social science data. Moreover, the integrated and interdisciplinary
nature of data requires collaboration among departments and organizations,
as well as with providers of data related to GIS and scientific
applications. These increasing and changing demands on the part of users
present challenges for institutions in allocating their limited resources.

In order to plan strategically to meet these needs, the MIT
Libraries
conducted a project to create a 3 year Data Services Plan. The
plan
contains goals for reference, instruction, collection
development,
personnel, facilities, computing, evaluation, and
implementation. This
presentation will describe the process of creating the Data
Services Plan,
including user studies, staff input, and research among peers
in the social
science data community. Additionally, it will discuss
challenges faced, the development of priorities, and strategies for
implementation.

Data Services Awareness and Use Survey: Assessing Secondary Data Needs at the University of Tennessee

Eleanor J. Read (University of Tennessee)

[abstract]

In recent years, the University of Tennessee has been striving to
increase awareness and use of data services provided by the Libraries. A
major move in that direction was hiring, for the first time, a data
services librarian who could provide more specialized and proactive
service to campus researchers. After three years with this new
arrangement, we decided to conduct a survey to learn more about our
secondary data users and to gauge the effectiveness of our various
promotional activities. This session will describe the process used to
gather information from faculty and graduate students in a variety of
departments about the use of secondary data in their research, and about
their awareness and use of the Libraries' Data Services. The results of
the survey, completed by about 375 respondents, will be used to help
plan future services and target groups that are potential data users.

Finding and using statistics can be challenging because such information
is located in multiple places and exists in large volumes. Efforts such
as FedStats (www.fedstats.gov)
address the challenge by providing gateways. Our project takes these
efforts further by proposing the Statistical Knowledge Network (SKN).

We envision a seamless network, where users have transparent access to
varied statistical information. The SKN would enable people to find
statistics without having to know particular sources, and provide
context for understanding and use.

Over the last 4 years, we have been developing the SKN: developing a
suite of tools for end-users, conceptualizing the architecture, and
conducting user studies. In this presentation, we present a status
report on our work to date and our future directions.

Acknowledgments: Other contributors to this work are Gary Marchionini
and Stephanie W. Haas of the University of North Carolina-Chapel Hill,
and Ben Shneiderman and Catherine Plaisant, of the University of
Maryland-College Park. This material is based upon work supported by the
National Science Foundation (NSF) under Grant EIA 0131824. Project
information is available at http://ils.unc.edu/govstat.

IASSIST Quarterly

Special issue: A pioneer data librarianWelcome
to the special volume of the IASSIST Quarterly (IQ (37):1-4, 2013).
This special issue started as exchange of ideas between Libbie
Stephenson and Margaret Adams to collect